AVEC 2016-Depression, Mood, and Emotion Recognition Workshop and Challenge

被引：440

作者：

Valstar, Michel ^{[1
]}

Gratch, Jonathan ^{[2
]}

Schuller, Bjoern ^{[3
,8
]}

Ringeval, Fabien ^{[3
,4
]}

Lalanne, Denis ^{[5
]}

Torres, Mercedes Torres ^{[1
]}

Scherer, Stefan ^{[2
]}

Stratou, Giota ^{[2
]}

Cowie, Roddy ^{[6
]}

Pantic, Maja ^{[7
,9
]}

机构：

[1] Univ Nottingham, Sch Comp Sci, Nottingham NG7 2RD, England

[2] Univ Southern Calif, ICT, Los Angeles, CA 90089 USA

[3] Univ Passau, Chair Complex & Intelligent Syst, Passau, Germany

[4] Univ Grenoble Alpes, Lab Informat, Grenoble, France

[5] Univ Fribourg, Human IST Res Ctr, CH-1700 Fribourg, Switzerland

[6] Queens Univ Belfast, Dept Psychol, Belfast BT7 1NN, Antrim, North Ireland

[7] Imperial Coll London, Intelligent Behav Understanding Grp, London, England

[8] Imperial Coll London, Dept Comp, London, England

[9] Univ Twente, EEMCS, Twente, Netherlands

来源：

PROCEEDINGS OF THE 6TH INTERNATIONAL WORKSHOP ON AUDIO/VISUAL EMOTION CHALLENGE (AVEC'16) | 2016年

关键词：

Affective Computing; Emotion Recognition; Speech; Facial Expression; Physiological signals; Challenge;

D O I：

10.1145/2988257.2988258

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

The Audio/Visual Emotion Challenge and Workshop (AVEC 2016) "Depression, Mood and Emotion" will be the sixth competition event aimed at comparison of multimedia processing and machine learning methods for automatic audio, visual and physiological depression and emotion analysis, with all participants competing under strictly the same conditions. The goal of the Challenge is to provide a common benchmark test set for multi-modal information processing and to bring together the depression and emotion recognition communities, as well as the audio, video and physiological processing communities, to compare the relative merits of the various approaches to depression and emotion recognition under well-defined and strictly comparable conditions and establish to what extent fusion of the approaches is possible and beneficial. This paper presents the challenge guidelines, the common data used, and the performance of the baseline system on the two tasks.

引用

页码：3 / 10

页数：8

共 42 条

[1] Local Gabor Binary Patterns from Three Orthogonal Planes for Automatic Facial Expression Recognition [J].

Almaev, Timur R. ;

Valstar, Michel F. .

2013 HUMAINE ASSOCIATION CONFERENCE ON AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION (ACII), 2013, :356-361

[2]

[Anonymous], P FG LIUBL SLOV MAY

[3]

[Anonymous], HDB PSYCHOBIOOGY

[4]

[Anonymous], 2015, Proceedings of the 5th International Workshop on Audio/Visual Emotion Challenge

[5]

[Anonymous], 2002, Manual and Investigators Guide

[6]

[Anonymous], 2013, Proceedings of the 21st ACM International Conference on Multimedia, DOI DOI 10.1145/2502081.2502224

[7]

[Anonymous], 2017, CAMBRIDGE HDB PSYCHO

[8]

[Anonymous], P RFMIR ICMI IST TUR

[9]

[Anonymous], 2015, P AVEC15 BRISB AUSTR

[10]

[Anonymous], P EMOSPACE FG SHANGH

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